The PhD Award
Sheffield Hallam University is inviting applications for this PhD project based in the Advanced Wellbeing Research Centre (AWRC), SHU. The project is part of our joint PhD programme with La Trobe University, Melbourne, Australia. Students on the joint PhD programme will be enrolled on a PhD at both institutions, with a supervisory team of academics from each institution. On successful completion, the candidate will be awarded a PhD jointly by both institutions.
This project is based at Sheffield Hallam, with an expectation that the successful candidate will spend up to 12 months at La Trobe University during the course of the project.
Further details and how to apply The awards will provide:
- Tuition fees at Home/UK rates
- A bursary at UKRI national doctoral stipend rates (£15,285 for 2020/21)
- One economy return air fare between the UK and La Trobe University
- Up to £600 to assist with personal/health insurance expenses while resident at La Trobe for 3 years of full-time study. These scholarships are not available for part-time study.
Behaviour change counselling such as Motivational Interviewing (MI) and Cognitive Behaviour Therapy (CBT) have been shown to consistently facilitate behavioural change in lifestyle behaviours, such as diet and physical activity (PA) that improve health and wellbeing (Breckon, 2015; O’Halloran et al., 2014). The benefits of regular PA are unequivocal, however there is little evidence to suggest that individuals that initiate these lifestyle behaviours will maintain change at recommended levels (Naar-King et al., 2014).
Indeed, evidence suggests that those individuals that do adopt lifestyle behaviour change (e.g. diet, PA, smoking, alcohol and medication adherence) as a result of participation in programmes utilising Behaviour Change Techniques (BCTs) such as self-monitoring and flexible goal setting, do not maintain behavioural changes with 75% of people dropping out within 12 weeks (Naar-King et al., 2014). Evidence suggests an over-emphasis by practitioners on PA initiation, neglecting long term-behaviour change strategies (Marcus et al., 2000). This approach has typically relied on passive information exchange (e.g. leaflets and signposting to guidelines) which has demonstrated little impact on long-term behaviour change and lifestyle modification.
There is an increasing interest and use of technologies to provide support for individuals in promoting health and wellbeing. This includes the use of Artificial Intelligence (AI) and machine learning (delivered via social robotics) which can be delivered at pace, in high volumes to large groups providing consistency, and provide extensive content thereby increasing the dose of evidence-based counselling strategies. Indeed, it is suggested that ongoing support from AI and machine learning can provide an approach that is flexible and sustainable leading to greater levels of maintenance.
Relying on the extensive support and expertise from staff at both universities , this PhD candidate will:
- undertake an extensive examination of how AI has been used to promote lifestyle behaviour change such as diet and PA and the efficacy of these strategies;
- develop and undertake preliminary testing of the feasibility of a lifestyle program comprising talking therapies embedded into an AI online program;
- and examine the efficacy of the lifestyle program comprising talking therapies embedded into AI online program to facilitate lifestyle behavioural change across a representative sample of adults within a workplace wellness scheme.
We are looking for a candidate who has an awareness of the use of lifestyle behaviour change (including PA counselling and talking therapies such as MI-CBT) and understands the core components of these that may be applied to digital platforms to form evidence-based AI and machine learning interventions. Support will be given in relation to the development of talking therapies and behaviour change regarding AI ecosystems. While an interest in the application of digital platforms to support behaviour change is desirable, there is NO expectation that the candidate has expertise in AI.
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